Porous materials are widely used in acoustic absorption applications, including building acoustics and noise control, among others. Accurate characterization of the acoustic behavior of actual materials is essential for understanding sound absorption and predicting performance. However, current methods predominanlty depend on experimental techniques, which are resource-intensive and time-consuming. These approaches often fail to facilitate the identification of optimal solutions or explain why certain materials outperform others. This study addresses these limitations by validating a numerical approach for predicting the sound absorption properties of porous materials. High-resolution 3-D geometries are obtained using X-ray micro-computed tomography, and simulations using GeoDICT predict key parameters which are applied to the Johnson–Champoux–Allard model to estimate acoustic absorption. Numerical predictions are validated using two experimental approaches: a direct method measuring normal incidence sound absorption coefficients with an impedance tube, and an indirect method determining the materials’ acoustic properties, incorporated into the JCA model for predicting the absorption coefficient. The results show strong agreement between numerical simulations and experimental measurements, confirming the reliability of the numerical approach. This validated methodology holds promise for characterizing virtual porous materials that have yet to be fabricated, thereby enabling numerical optimization of porous structures.
Hajj et al. (Tue,) studied this question.